Project Summary Proteogenomic characterization of human tumors seeks to explain how complex genomic alterations drive the hallmarks of cancer through mass spectrometry based proteomic analysis. The field has been accelerated by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) who performed proteomic analyses for breast, colorectal and ovarian tumors and integrated the data with genomic information provided by the Cancer Genome Atlas (TCGA). Our Vanderbilt team conducted the colorectal cancer study and published the first paper on proteogenomic characterization of human cancer in the journal Nature. Data analysis approaches pioneered by us also were used in the CPTAC breast and ovarian cancer studies. Results from all three studies successfully demonstrated the value of integrative proteogenomic analyses in achieving a more complete understanding of cancer biology. Based on this proof of concept, the new CPTAC program seeks to expand the proteogenomic approach to more cancer types and to diverse types of samples including pre- and post-treatment clinical specimens, cultured cells, and patient-derived xenografts (PDXs). This application proposes an integrative proteogenomic data analysis center (iPGDAC) built on our established expertise and resources. The overarching goal of the iPGDAC is to analyze data generated by CPTAC and related resources to better understand cancer biology and to improve cancer treatment. To comprehensively exploit all CPTAC data, we propose three tiers of data analysis. Tier 1 analyses will integrate proteomic and genomic data generated from individual studies. These analyses will identify variant peptides and proteins as candidate biomarkers or therapeutic targets, will predict patient prognosis and response to therapy based on multi-omics data, and will reveal mechanisms of drug action and acquired drug resistance to drive rational drug combinations. Tier 2 analyses will integrate data between preclinical models and human tumors to enable effective translation of experimental findings to the clinic. Tier 3 analyses will integrate data across different cancer types to identify common and cancer type-specific protein signatures and networks. We will make our computational tools and analysis results publically available in two integrated proteogenomic data analysis systems, which will facilitate the collaborative identification of candidate biomarkers by all CPTAC investigators and will broaden the impact of the CPTAC program. The iPGDAC brings to the CPTAC network a fully integrated, completely established program with expertise in all the critical areas specified by the RFA. We have a proven track record of leadership in computational proteogenomics and successful collaboration in the CPTAC network, and we expect to broadly advance the field through this project.